论文标题
大脑是否使用相位计算作为量子相计算机?
Does the brain function as a quantum phase computer using phase ternary computation?
论文作者
论文摘要
在这里,我们提供的证据表明,神经交流的基本基础是由能够以足够的时间精度计算的压力脉冲/孤子来得出的,以克服任何处理误差。神经系统中的信号传导和计算是复杂且现象不同的。动作电位是塑性的,这使得动作电位峰成为神经计算的不适当固定点,但是动作电位阈值适合此目的。此外,尖峰神经元的时间计时的神经模型低于克服处理误差所需的速率。以视网膜处理为例,我们证明了基于电缆理论的当代神经传导理论是不合适的,无法说明视网膜的全部功能所必需的短期计算时间,并暗示大脑的其余部分。此外,电缆理论不能在动作电位的传播中发挥作用,因为在激活阈值中,激活位点的电荷不足,无法静电开放的连续离子通道。大脑神经网络的解构表明,它是一组量子相计算机的成员,该计算机是Turing Machine最简单的:大脑是基于相位三元计算的另一个。但是,尝试使用基于图灵的机制无法解决视网膜的编码或智能的计算,因为基于图灵的计算机的技术在根本上是不同的。我们证明,大脑神经网络中的编码是基于量子的,其中量子具有时间变量,相碱变量可启用相位三元计算,如先前在视网膜中所示。
Here we provide evidence that the fundamental basis of nervous communication is derived from a pressure pulse/soliton capable of computation with sufficient temporal precision to overcome any processing errors. Signalling and computing within the nervous system are complex and different phenomena. Action potentials are plastic and this makes the action potential peak an inappropriate fixed point for neural computation, but the action potential threshold is suitable for this purpose. Furthermore, neural models timed by spiking neurons operate below the rate necessary to overcome processing error. Using retinal processing as our example, we demonstrate that the contemporary theory of nerve conduction based on cable theory is inappropriate to account for the short computational time necessary for the full functioning of the retina and by implication the rest of the brain. Moreover, cable theory cannot be instrumental in the propagation of the action potential because at the activation-threshold there is insufficient charge at the activation site for successive ion channels to be electrostatically opened. Deconstruction of the brain neural network suggests that it is a member of a group of Quantum phase computers of which the Turing machine is the simplest: the brain is another based upon phase ternary computation. However, attempts to use Turing based mechanisms cannot resolve the coding of the retina or the computation of intelligence, as the technology of Turing based computers is fundamentally different. We demonstrate that that coding in the brain neural network is quantum based, where the quanta have a temporal variable and a phase-base variable enabling phase ternary computation as previously demonstrated in the retina.